Feb 28, 2005 - The Literature Review has been divided into six main topic areas: (a) Broccoli ...... However in broccoli cultivar 'Galaxy', the developmental stage most sensitive to heat. (1 week at 35 o ...... S1 S2 S3 S4 S5 S6 S7 S8. Fig. 3.1.
Effect of temperature and photoperiod on broccoli development, yield and quality in south-east Queensland
By
Daniel Kean Yuen Tan
B. App. Sc. (Hort. Tech.) (First Class Hons.) The University of Queensland
A Thesis submitted for the degree of Doctor of Philosophy in The University of Queensland
School of Land and Food
June 1999
ii
DECLARATION OF ORIGINALITY
This thesis reports the original work of the author, except otherwise acknowledged. It has not been submitted previously at this or any other University.
Daniel K.Y. Tan
iii
ABSTRACT Broccoli is a vegetable crop of increasing importance in Australia, particularly in south-east Queensland and farmers need to maintain a regular supply of good quality broccoli to meet the expanding market. However, harvest maturity date, head yield and quality are all affected by climatic variations during the production cycle, particularly low temperature episodes. There are also interactions between genotype and climatic variability. A predictive model of ontogeny, incorporating climatic data including frost risk, would enable farmers to predict harvest maturity date and select appropriate cultivar – sowing date combinations.
The first stage of this research was to define floral initiation, which is fundamental to predicting ontogeny. Scanning electron micrographs of the apical meristem were made for the transition from the vegetative to advanced reproductive stage. During the early vegetative stage (stage 1), the apical meristem was a small, pointed shoot tip surrounded by leaf primordia. The transitional stage (stage 2) was marked by a widening and flattening to form a dome-shaped apical meristem.
In the floral
initiation stage (stage 3), the first-order floral primordia were observed in the axils of the developing bracts. Under field conditions, the shoot apex has an average diameter of 500 ± 3 µm at floral initiation and floral primordia can be observed under a light microscope.
Sub-zero temperatures can result in freezing injury and thereby reduce head yield and quality. In order to predict the effects of frosts, it is desirable to know the stages of development at which plants are most susceptible. Therefore, the effects of sub-zero temperatures on leaf and shoot mortality, head yield and quality were determined after exposure of plants to a range of temperatures for short periods, at different stages of development (vegetative, floral initiation and buttoning). Plants in pots and in the field were subjected to sub-zero temperature regimes from –1 °C to –19 °C. Extracellular ice formation was achieved by reducing temperatures slowly, at a rate of -2 °C per hour. The floral initiation stage was most sensitive to freezing injury, as yields were significantly reduced at –1 °C and –3 °C, and shoot apices were killed at –5 °C. There was no significant yield reduction when the inflorescence buttoning
iv
stage was subjected to –1 °C and –3 °C. Although shoot apices at buttoning survived the –5 °C treatment, very poor quality heads of uneven bud size were produced as a result of arrested development. The lethal temperature for pot-grown broccoli was between –3 °C and –5 °C, whereas the lethal temperature for field-grown broccoli was between –7 °C and –9 °C. The difference was presumably due to variation in cold acclimation. Freezing injury can reduce broccoli head yield and quality, and retard plant growth. Crop development models based only on simple thermal time without restrictions will not predict yield or maturity if broccoli crops are frostdamaged.
Field studies were conducted to develop procedures for predicting ontogeny, yield and quality. Three cultivars, (‘Fiesta’, ‘Greenbelt’ and ‘Marathon’) were sown on eight dates from 11 March to 22 May 1997, and grown under natural and extended (16 h) photoperiods in a sub-tropical environment at Gatton College, south-east Queensland, under non-limiting conditions of water and nutrient supply.
Daily
climatic data, and dates of emergence, floral initiation, harvest maturity, together with yield and quality were obtained. Yield and quality responses to temperature and photoperiod were quantified.
As growing season mean minimum temperatures
decreased, fresh weight of tops decreased while fresh weight harvest index increased linearly. There was no definite relationship between fresh weight of tops or fresh weight harvest index and growing season minimum temperatures ≥ 10 °C. Genotype, rather than the environment, mainly determined head quality attributes. ‘Fiesta’ had the best head quality, with higher head shape and branching angle ratings than ‘Greenbelt’ or ‘Marathon’. Bud colour and cluster separation of ‘Marathon’ were only acceptable for export when growing season mean minimum temperatures were < 8 °C. Photoperiod did not influence yield or quality in any of the three cultivars. A better understanding of genotype and environmental interactions will help farmers optimise yield and quality, by matching cultivars with time of sowing.
Crop developmental responses to temperature and photoperiod were quantified from emergence to harvest maturity (Model 1), from emergence to floral initiation (Model 2), from floral initiation to harvest maturity (Model 3), and in a combination of Models 2 and 3 (Model 4). These thermal time models were based on optimised base
v
and optimum temperatures of 0 and 20 °C, respectively.
These optimised
temperatures were determined using an iterative optimisation routine (simplex). Cardinal temperatures were consistent across cultivars but thermal time of phenological intervals were cultivar specific. Sensitivity to photoperiod and solar radiation was low in the three cultivars used.
Thermal time models tested on
independent data for five cultivars (‘Fiesta’, ‘Greenbelt’, ‘Marathon’, ‘CMS Liberty’ and ‘Triathlon’) grown as commercial crops on the Darling Downs over two years, adequately predicted floral initiation and harvest maturity.
Model 4 provided the best prediction for the chronological duration from emergence to harvest maturity.
Model 1 was useful when floral initiation data were not
available, and it predicted harvest maturity almost as well as Model 4 since the same base and optimum temperatures of 0 °C and 20 °C, respectively, were used for both phenological intervals. Model 1 was also generated using data from 1979-80 sowings of three cultivars (‘Premium Crop’, ‘Selection 160’ and ‘Selection 165A’). When Model 1 was tested with independent data from 1983-84, it predicted harvest maturity well. Where floral initiation data were available, predictions of harvest maturity were most precise using Model 3, since the variation, which occurred from emergence to floral initiation, was removed. Prediction of floral initiation using Model 2 can be useful for timing cultural practices, and for avoiding frost and high temperature periods.
This research has produced models to assist broccoli farmers in crop scheduling and cultivar selection in south-east Queensland. Using the models as a guide, farmers can optimise yield and quality, by matching cultivars with sowing date. By accurately predicting floral initiation, the risk of frost damage during floral initiation can be reduced by adjusting sowing dates or crop management options. The simple and robust thermal time models will improve production and marketing arrangements, which have to be made in advance.
The thermal time models in this study,
incorporating frost risk using conditional statements, provide a foundation for a decision support system to manage the sequence of sowings on commercial broccoli farms.
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Additional Publications of Candidate Relevant to Thesis Tan, D.K.Y., Wearing, A.H., Rickert, K.G. and Birch, C.J. (1997).
A systems
approach to developing a model that predicts crop ontogeny and maturity in broccoli in south-east Queensland.
In ‘Third Australia and New Zealand
Systems Conference Proceedings: Linking People, Nature, Business and Technology.’
(Eds Wollin, A.S. and Rickert, K.G.).
pp. 179-187. (The
University of Queensland: Gatton.)
Tan, D.K.Y., Wearing, A.H., Rickert, K.G. and Birch, C.J. (1998). Detection of floral initiation in broccoli (Brassica oleracea L. var. italica Plenck) based on electron micrograph standards of shoot apices.
Australian Journal of
Experimental Agriculture 38(3): 313-318.
Tan, D.K.Y., Wearing, A.H., Rickert, K.G., Birch, C.J. and Joyce, D.C. (1999). Freeze-induced reduction of broccoli yield and quality. Australian Journal of Experimental Agriculture 39(6) (In Press.)
Tan, D.K.Y., Wearing, A.H., Rickert, K.G. and Birch, C.J. (1999). Broccoli yield and quality can be determined by cultivar and temperature but not photoperiod in south-east Queensland. Australian Journal of Experimental Agriculture 39(7) (In Press.)
Tan, D.K.Y., Birch, C.J., Wearing, A.H. and Rickert, K.G. (1999).
Predicting
broccoli development: I. Development is predominantly determined by temperature rather than photoperiod. Scientia Horticulturae (accepted.)
Tan, D.K.Y., Birch, C.J., Wearing, A.H. and Rickert, K.G. (1999).
Predicting
broccoli development: II. Comparison and validation of thermal time models. Scientia Horticulturae (accepted.)
vii
Table of Contents TITLE Declaration of Originality
(ii)
Abstract
(iii)
Additional Publications of Candidate Relevant to Thesis
(vi)
Table of Contents
(vii)
List of Tables
(xvi)
List of Figures
(xix)
List of Plates
(xxv)
Abbreviations
(xxvi)
Terminology
(xxvii)
Acknowledgments
(xxviii)
Chapter 1 General Introduction 1.1
Broccoli in Australia
1
1.2
Systems approach to define the problem
1
1.3
Yield and quality
5
1.4
Prediction of ontogeny and maturity
5
1.5
Objectives of this research
7
1.6
Steps in this research
9
Chapter 2 Review of Literature
2.1
Introduction
11
2.2
Broccoli development
11
2.2.1
History and botany
11
viii
2.2.2
Phenological development and ontogeny
13
(a) Developmental stage 1
15
(b) Developmental stage 2
15
(c) Developmental stage 3
17
2.3
Yield and quality of broccoli
18
2.3.1
Yield and harvest index
18
2.3.2
Quality
20
(a) Bractiness
21
(b) Hollow stem
21
(c) Starring
22
(d) Albugo candida (White Blister)
22
(e) Colour
22
2.4
Effect of temperature
23
2.4.1
Cardinal temperatures for development
23
2.4.2
Effect of temperature on phenological development
24
(a) Seed vernalisation
24
(b) Developmental stage 1
25
(c) Developmental stage 2
26
(i)
Beginning of receptiveness
26
(ii)
Vernalisation requirement
28
(iii)
Inductive temperature range
29
(iv)
Premature floral initiation and flowering
29
(a) Developmental stage 3
30
Effect of temperature on quality
31
(a) Effect of low temperature on quality
32
(b) Effect of high temperature on quality
32
2.5
Effect of sub-zero temperatures
33
2.5.1
Frost
33
(a) Radiation frost
33
(b) Black frost
34
2.4.3
ix
2.5.2
2.5.3
2.5.4
(c) Advection frost
35
Freezing injury
35
(a) Intracellular freezing
35
(b) Intercellular freezing
36
Resistance to freezing injury
37
(a) Freezing avoidance
37
(i)
By antifreeze or dehydration
37
(ii)
Supercooling
38
(iii)
Thermal insulation by wrapping-leaves
38
(a) Freezing tolerance
38
Cold acclimation (hardening)
39
(a) Physiological factors during cold acclimation
39
(i)
Osmotic concentration
39
(ii)
Water content
40
(iii)
Lipids
40
(iv)
Proteins
40
(v)
Growth regulators
40
(vi)
Photosynthesis
41
(a) Environmental factors
41
(i)
Temperature
41
(ii)
Light
42
(iii)
Photoperiod
42
(a) Plant tissue
42
(b) Stage of development
43
(i)
Vegetative stage
43
(ii)
Floral initiation stage
43
(iii)
Inflorescence development stage
44
2.6
Effect of other environmental factors
44
2.6.1
Effect of photoperiod
44
2.6.2
Effect of solar radiation
45
2.7
Models for predicting development and maturity
46
2.7.1
Forthside model
47
x
2.7.2
Gatton models
49
(a) Non-linear, rectangular hyperbola model
49
(b) Simple thermal time model
50
(c) Modified thermal time (Barger System) model
50
(d) Comparison of Gatton models
50
2.7.3
Scottish model
51
2.7.4
Massey model
52
2.7.5
Reading model
53
2.7.6
Kagawa model
54
2.7.7
Wellesbourne vernalisation model
55
2.7.8
Wellesbourne maturity prediction models
56
(a) Quadratic transplanting to HM model
56
(b) Maturity prediction from FI to HM
56
2.7.9
Clemson model
58
2.7.10
Aarslev model
59
2.7.11
Evaluation of prediction models
59
2.8
Conclusions
61
Chapter 3 General Materials and Methods
3.1
Field experiment with photoperiod extension
62
3.2
Commercial farm crops
66
3.3
Data collection
66
3.3.1
Climatic data
66
3.3.2
Crop ontogeny
69
3.3.3
Leaf number
69
3.3.4
Head quality
70
3.4
Data analysis
70
xi
3.5
Summary
72
Chapter 4 Detection of floral initiation based on electron micrograph standards of shoot apices
4.1
Introduction
73
4.2
Materials and methods
74
4.2.1
Source of samples for scanning electron microscopy
75
4.2.2
Scanning electron microscopy
75
4.2.3
Source of samples for light microscope
75
4.2.4
Light microscopy
76
4.2.5
Statistical analysis
76
4.3
Results
77
4.3.1
Morphological development of the apical meristem
77
4.3.2
Definition of the apex diameter at initiation
79
4.4
Discussion
80
4.4.1
Morphological development of the apical meristem
80
4.4.2
Diameter of the apex at initiation
82
4.5
Conclusions
83
Chapter 5 Freeze-induced reduction of broccoli yield and quality
5.1
Introduction
84
5.2
Materials and methods
86
5.2.1
Field-grown broccoli (Experiments 1 and 2)
86
5.2.2
Pot experiment (Experiment 3)
86
5.2.3
Sub-zero temperature treatments
87
xii
5.2.4
Data collection
88
(a) Crop ontogeny
88
(b) Relative electrical conductivity (REC)
88
(c) Vital staining
89
(d) Shoot apex, leaf lamina and petiole mortality
89
(e) Yield and quality
90
(f) Ambient temperature
90
5.2.5
Data analysis
91
5.3
Results
92
5.3.1
Electrolyte leakage of field-grown broccoli (Experiments 1 & 2)
92
5.3.2
Mortality of pot-grown broccoli (Experiment 3)
94
5.3.3
Yield and quality of pot-grown broccoli (Experiment 3)
98
5.4
Discussion
101
5.4.1
Yield and quality reduction
101
5.4.2
Tissue damage
102
5.4.3
Cold acclimation
103
5.5
Conclusions
104
Chapter 6
Influence of temperature and photoperiod on
broccoli yield and quality
6.1
Introduction
105
6.2
Materials and methods
106
6.2.1
Quality attributes of commercial grades
106
6.2.2
Field experiment with photoperiod extension
107
6.2.3
Data collection
108
6.2.4
Data analysis
109
6.3
Results
109
xiii
6.3.1
Quality attributes of commercial grades
109
6.3.2
Yield
110
6.3.3
Quality
112
6.3.4
Photoperiod
116
6.4
Discussion
117
6.4.1
Yield
117
6.4.2
Quality
117
6.4.3
Photoperiod
118
6.5
Conclusions
119
Chapter
7
Broccoli
development
is
predominantly
determined by temperature
7.1
Introduction
120
7.2
Materials and methods
123
7.2.1
Field experiment with photoperiod extension
123
7.2.2
Commercial farm crops for testing the model
123
7.2.3
Data collection
124
7.2.4
Data analysis
124
7.3
Results
125
7.3.1
Photoperiod, cultivar and sowing date effects
125
7.3.2
Temperature response
128
7.3.3
Photoperiod response during EFI
131
7.3.4
Total solar radiation
132
7.3.5
Total leaf number
132
7.3.6
Accuracy of fitted values from optimised Tbase and Topt
134
7.3.7
Evaluation of model against independent farm data
135
7.4
Discussion
138
xiv
7.4.1
Optimised temperature coefficients
138
7.4.2
Photoperiod response
140
7.4.3
Solar radiation response
141
7.4.4
Leaf number
142
7.5
Conclusions
144
Chapter 8
Comparison and validation of thermal time
models from emergence to harvest maturity
8.1
Introduction
145
8.2
Materials and methods
146
8.2.1
Field experiment with photoperiod extension
146
8.2.2
Commercial farm crops for testing the models
146
8.2.3
Farm records
147
8.2.4
Titley’s experiments
147
8.2.5
Data analysis
148
8.3
Results
148
8.3.1
Time from sowing to harvest maturity
148
8.3.2
Photoperiod, cultivar and sowing date effects
149
8.3.3
Accuracy of fitted values from optimised Tbase and Topt
151
8.3.4
Evaluation of models against independent farm data
154
8.3.5
Evaluation of EHM model against Titley’s data
155
8.4
Discussion
158
8.5
Conclusions
159
Chapter 9 General Discussion
9.1
Detection of floral initiation
161
xv
9.2
Yield and quality
161
9.3
Thermal time models
163
9.4
Applications of thermal time models
165
9.5
Cultivar selection
167
9.6
Conclusions
168
9.7
Suggested future work
170
Bibliography
171
xvi
List of Tables
Table No. 2.1
Page Morphological changes in broccoli in relation to leaf number and plant age (adapted from Gauss and Taylor 1969a)
15
2.2
Broccoli apex diameter at floral initiation
16
2.3
Selected reports of broccoli marketable head yield in studies covering a range of environmental and cultural conditions.
19
Base, optimum and maximum temperatures for the development of broccoli
24
Base, optimum and maximum temperatures for germination of broccoli
25
Effect of vernalisation (inductive temperature range and exposure time) on floral initiation of broccoli
28
Growing season mean temperatures (°C) at which broccoli head quality is unacceptable at the range of temperatures experienced during 50 sowing dates at Charleston, S.C., USA from 1990 to 1992 (adapted from Dufault 1996)
32
Models for the prediction of phenological development and maturity of broccoli.
48
Apex description during the transition from a vegetative to reproductive apex for broccoli.
79
Mean apex diameter (µm) of broccoli at the five morphological stages during the transition from a vegetative to reproductive apex measured from scanning electron micrographs. The standard error (s.e.), maximum and minimum of the range are included. Mean apex diameter between the morphological stages were significantly different at P=0.01 using the nonparametric Kruskal-Wallis test of ranked diameter.
80
Summary of sub-zero temperature treatments (ambient, -1, -3, -5, and –7 °C) and stage of development (floral initiation and buttoning) critical temperature ranges (°C) for pot-grown broccoli where damage or destruction was observed for >95% of the sample population in binomial vital staining, lamina mortality index, lamina destruction index, petiole mortality index, petiole destruction index or shoot apex destruction index
97
2.4
2.5
2.6
2.7
2.8
4.1
4.2
5.1
xvii
data. 5.2
6.1
6.2
7.1
Effect of sub-zero temperature treatments (ambient, -1, -3, -5, and -7 °C) and stage of development (floral initiation and buttoning) on yield: head diameter (mm), head fresh weight (g) and head dry weight (g), and quality ratings: bud colour (1-5), bud evenness (1-5) and cluster separation (1-5) for pot-grown broccoli. Means followed by the same letter are not significantly different at P = 0.05 by Fisher’s protected l.s.d. test and conducted only when F-test probability was significant at P ≤ 0.05. Data presented in this figure are sub-zero temperature treatment by stage of development interaction means (n = 10). Dash (-) indicates no quality ratings were made as plants were killed resulting in no yield.
99
Head yield and quality attributes of five broccoli grades (Export Japan, Export South-east Asia, Domestic Chain Stores, Domestic Central Markets Large and Small), expressed as head fresh weight (g head-1), head diameter (mm), head shape (1-5), branching angle (1-5) and cluster separation (1-5) ratings packed by eight packers in a packing house near Brookstead, south-east Queensland. Means of grades are averaged over eight packers (n = 40). L.s.d. values are at P=0.05 using Fisher’s protected l.s.d. tests for grade main effect. Means followed by the same letter within the same row are not significantly different at P=0.05.
110
Head quality attributes of three broccoli cultivars (‘Fiesta’, ‘Greenbelt’ and ‘Marathon’), expressed as head shape (1-5), branching angle (1-5), cluster separation (1-5) and bud evenness (1-5) ratings, bud size (mm), bractiness (number of bracts protruding through head), percent head dry weight (%) (dry/fresh weight), and principal components 1 and 2 (PC1 & PC2) grown under a range of photoperiod and temperature regimes at Gatton College, south-east Queensland. Means of cultivars are averaged over two photoperiods (natural and 16 h) and eight sowing dates (n = 48). L.s.d values are at P=0.05, using Fisher’s protected l.s.d. tests for the cultivar main effect. Means followed by the same letter within the same row are not significantly different at P=0.05.
113
Main and interactive effects of photoperiod extension (PP), sowing date (SD) and cultivar (CV) on the chronological time (days), thermal time (°C d) and accumulated solar radiation (MJ m-2) during the interval from emergence to floral initiation, and total leaf number in broccoli [**, *, n.s. for P
